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Comovements and asymmetric tail dependence in state housing prices in the USA: A nonparametric approach

机译:美国州住房价格的联动和尾部不对称依赖:一种非参数方法

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摘要

We reexamine the methods used in estimating comovements among US regional home prices and find that there are insufficient moments to ensure a normal limit necessary for employing the quasi-maximum likelihood estimator. Hence we propose applying the self-weighted quasi-maximum exponential likelihood estimator and a bootstrap method to test and account for the asymmetry of comovements as well as different magnitudes across state pairs. Our results reveal interstate asymmetric tail dependence based on observed house price indices rather than residuals from fitting autoregressive-generalized autoregressive conditional heteroskedasticity (AR-GARCH) models.
机译:我们重新检查了用于估计美国区域房价之间的联动变化的方法,发现没有足够的时间来确保采用准最大似然估计器所需的正常极限。因此,我们建议使用自加权的拟最大指数似然估计器和自举方法来测试和考虑共运动的不对称性以及状态对之间的不同幅度。我们的结果表明,基于观察到的房价指数,而不是拟合自回归-广义自回归条件异方差(AR-GARCH)模型的残差,得出州际不对称尾巴依赖性。

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  • 来源
    《Journal of applied econometrics》 |2019年第5期|843-849|共7页
  • 作者单位

    Georgia State Univ, Dept Risk Management & Insurance, Atlanta, GA 30303 USA;

    Georgia State Univ, Dept Risk Management & Insurance, Atlanta, GA 30303 USA;

    Georgia State Univ, Dept Real Estate, Atlanta, GA 30303 USA;

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